Ethical consumption: Influencing factors of consumer´s intention to purchase Fairtrade roses
Berki-Kiss, D.; Menrad, K. (2022)
Cleaner and Circular Bioeconomy 2, 100008, S. 1-9.
DOI: 10.1016/j.clcb.2022.100008
Open Access
The role emotions play in consumer intentions to make pro-social purchases in Germany – An augmented theory of planned behavior model
Berki-Kiss, D.; Menrad, K. (2022)
Sustainable Production and Consumption 29, S. 79-89.
DOI: 10.1016/j.spc.2021.09.026
Open Access
Although, sustainable consumption is gaining in relevance for consumers and retailers in Germany, pro-social consumption is still often neglected. Therefore, this study investigates factors influencing the purchase intention of German flower buyers in relation to Fairtrade-cut roses based on an online survey of 1,201 flower buyers in retail shops in 2017. As a basic theoretical framework, the Theory of Planned Behavior (TPB) was utilized and extended with two additional constructs. The addition of emotions and perceived consumer effectiveness reveals a strong explanatory power of the model proposed. Data analysis via partial least square structural equation modeling (PLS-SEM) suggests that emotions and subjective norm are the two most influential determinants of intention to purchase Fairtrade roses. However, emotions also significantly influence all determinants of behavioral intention introduced to the extended model. The findings of this study can be used to fine-tune marketing and communication activities related to pro-social and Fairtrade products.
Financing wind energy projects: An extended theory of planned behavior approach to explain private households’ wind energy investment intentions in Germany
Gamel, J.; Bauer, A.; Decker, T.; Menrad, K. (2022)
Renewable Energy Volume 182 (January 2022), S. 592-601.
DOI: 10.1016/j.renene.2021.09.108
Socially responsible investment (SRI) is an investment strategy which complies with ethical, social, environmental or corporate governance criteria. Investments in renewable energies are commonly regarded as complying with SRI principles. This study aims to deepen the understanding of individuals' intentions to invest in wind energy. As an underlying framework the Theory of Planned Behavior's constructs attitude, subjective norm and perceived behavioral control were used and statistically tested with an online-survey of 592 participants in 2014. Further, this theory was extended by adding the constructs consumption profile and investor profile to the framework. With the inclusion of the two additional constructs the theoretical model turns to be very suitable as it doubled the share of explained variance of behavioral intention from 25% to 50% compared to the Theory of Planned Behavior. The analysis further shows that subjective norms, perceived behavioral control, consumption profile and investor experience have statistically significant influence on investment intentions in wind energy. However, attitudes towards wind energy investments are not a significant predictor of investment intentions. We conclude that, apart from the scientific implications of our results, our findings have practical applications for the conceptual design of wind energy investments.
Machine Learning Outperforms Classical Forecasting on Horticultural Sales Predictions
Haselbeck, F.; Killinger, J.; Menrad, K.; Hannus, T.; Grimm, D. (2022)
Machine Learning with Applications Volume 7, 100239 (2022).
DOI: 10.1016/j.mlwa.2021.100239
Open Access
Forecasting future demand is of high importance for many companies as it affects operational decisions. This is especially relevant for products with a short shelf life due to the potential disposal of unsold items. Horticultural products are highly influenced by this, however with limited attention in forecasting research so far. Beyond that, many forecasting competitions show a competitive performance of classical forecasting methods. For the first time, we empirically compared the performance of nine state-of-the-art machine learning and three classical forecasting algorithms for horticultural sales predictions. We show that machine learning methods were superior in all our experiments, with the gradient boosted ensemble learner XGBoost being the top performer in 14 out of 15 comparisons. This advantage over classical forecasting approaches increased for datasets with multiple seasons. Further, we show that including additional external factors, such as weather and holiday information, as well as meta-features led to a boost in predictive performance. In addition, we investigated whether the algorithms can capture the sudden increase in demand of horticultural products during the SARS-CoV-2 pandemic in 2020. For this special case, XGBoost was also superior. All code and data is publicly available on GitHub: https://github.com/grimmlab/HorticulturalSalesPredictions.
The Influence of Climate Attitudes and Subjective and Social Norms on Supermarket Consumers' Intention Toward Climate-Friendly Food Consumption
Emberger-Klein, A.; Schöps, J.; Menrad, K. (2021)
Frontiers in Sustainable Food Systems 5, 764517, S. 1-12.
DOI: 10.3389/fsufs.2021.764517
Open Access
Determining the Distinguishing Features of Different Eating Action Types in Germany Using a Mixed-Method Approach
Lampmann, L.; Emberger-Klein, A.; Menrad, K. (2021)
Frontiers in Nutrition.
DOI: 10.3389/fnut.2021.720392
Open Access
Some like it tailor-made: The effectiveness of personalized coupons for lower-calorie food choices at a university canteen
Nguyen, M.; Emberger-Klein, A.; Menrad, K. (2021)
International Journal of Consumer Studies.
DOI: 10.1111/ijcs.12723
Open Access
Asymmetric effects of price discounts on low-fat versus full-fat products: A choice-based segmentation of pudding buyers in Germany
Nguyen, M.; Emberger-Klein, A.; Menrad, K. (2021)
Vortrag bei Konferenz „Food Reformulation – Regulation and Marketing“, 17.-18.6.2021 (digitale Konferenz).
Verbraucherreaktionen bei Plastik und dessen Vermei-dungsmöglichkeiten am Point of Sale (VerPlaPoS)
Decker, T.; Lippl, M.; Albrecht, S.; Bauer, K.; Drechsel, P.; Frommeyer, B.; Habermehl, T.; Heider, D.; Holterbosch, J.; Klaene, K.; Koch, J.; Lorenz, M.; Menrad, K.; Muth, L.; Niedermeier, A.; Sängerlaub, S.; Scagnetti, C.; Schewe, G.; Tornow, M.; van den Adel, F.; von Gehlen, K. (2021)
Decker, T.; Lippl, M.; Albrecht, S.; Bauer, K.; Drechsel, P.; Frommeyer, B....
Abschlussbericht, 177 S.
Is there a relationship between implicit motives and eating action types: An exploratory study in Germany
Lampmann, L.; Emberger-Klein, A.; Menrad, K. (2021)
Journal of Consumer Culture, S. 1-19.
DOI: 10.1177%2F14695405211013954
Open Access
Marketing of biodegradable plastic products
Menrad, K. (2021)
Vortrag auf SAPEA/EU: Biodegradability of plastics – Social sciences webinar. 21.5.2021 (digitale Konferenz).
The effects of customized price discounts on choices of low-fat dairy products: A German household panel study
Nguyen, M.; Emberger-Klein, A.; Menrad, K. (2021)
Kompetenzcluster der Ernährungsforschung. Cluster Conference Competence Cluster Nutrition Research, 17.-19.5.2021, S. 116.
The effects of customized price discounts on choices of low-fat dairy products: A German household panel study
Nguyen, M.; Emberger-Klein, A.; Menrad, K. (2021)
Poster bei Cluster Conference Competence Cluster Nutrition Research, 17.-19.05.2021 (digitale Konferenz).
PlantGrid – Digitale Management-Unterstützungssysteme für kleine und mittelständische Unternehmen in Wertschöpfungsketten von Zierpflanzen, Stauden und Schnittblumen
Menrad, K.; Haselbeck, F.; Berki-Kiss, D.; Decker, T.; Grimm, D.; Hannus, T.; Sparke, K.; Lehberger, M.; Drechsler, M.; Holzapfel, A.; Schröder, S.; Neu, G.; Bertlich, F. (2021)
Menrad, K.; Haselbeck, F.; Berki-Kiss, D.; Decker, T.; Grimm, D.; Hannus, T....
Vortrag auf Statusworkshop der FuE-Projekte im BMEL-Förderschwerpunkt Gartenbau 4.0. 4.-5.5.2021 (digitale Konferenz).
Consumer Preferences in Germany for Bio-Based Apparel With Low and Moderate Prices, and the Influence of Specific Factors in Distinguishing Between These Groups
Stahl, F.; Emberger-Klein, A.; Menrad, K. (2021)
Frontiers in Sustainability 2, 624913.
DOI: 10.3389/frsus.2021.624913
Open Access
Drivers and barriers for purchasing green fast-moving consumer goods: A study of consumer preferences of glue sticks in Germany
Niedermeier, A.; Emberger-Klein, A.; Menrad, K. (2021)
Journal of Cleaner Production 284, 124804.
DOI: 10.1016/j.jclepro.2020.124804
Which factors distinguish the different consumer segments of green Fast Moving Consumer Goods in Germany?
Niedermeier, A.; Emberger-Klein, A.; Menrad, K. (2021)
Business Strategy and Environment 30 (4), S. 1823-1838.
DOI: 10.1002/bse.2718
Open Access
Nachhaltigkeit und Konsum im Lichte der Corona-Krise
Menrad, K. (2021)
TUM Forum Sustainability - Wissenschaft, Vernunft & Nachhaltigkeit: Denkanstöße für die Zeit nach Corona, TU München, S. 182-185.
Personalized coupons for lowercalorie fast-food choices among young German adults and the influence of consumers´nutritional attitudes on promotion effectiveness
Nguyen, M.; Emberger-Klein, A.; Menrad, K. (2020)
British Food Journal 123 (4), S. 1413-1432.
DOI: 10.1108/BFJ-08-2020-0709
Beyond risk and return: What motivates environmentally friendly or harmful student fund investments in Germany?
Menrad, K.; Bauer, A. (2020)
Energy Research & Social Science 67, 101509.
DOI: 10.1016/j.erss.2020.101509
Prof. Dr. Klaus Menrad
Hochschule Weihenstephan-Triesdorf
T +49 9421 187-200 klaus.menrad[at]hswt.de